Bibliographic record
Abstract
This article reflects on the evolution of Canada's whole-of-government approach in the context of international cooperation in Afghanistan.Although the effort resulted in great gains when Canadian Forces were actively involved in combat roles, the nation does not seem interested in maintaining the capability as a framework for quickly responding to current or future international crises.P olitical scientist Stephen M. Saideman captured the incomplete state of Canada's post-Afghanistan learning with this simple advice: Canada should "not to do it again." 1 Five years after the commitment ended, national introspection has been left to scholars attempting to understand the consequential changes.To comprehend the modifications resulting from Canada's experiences in Afghanistan, one must understand the shifts that occurred within the government during the conflict and then scrutinize the outcomes.2 Finally, reflection can occur to determine if the efforts changed how Canada engages in post-Afghanistan missions and if there are lessons that have been learned and implemented.3 The unprecedented level of interdepartmental cooperation and involvement that was necessary to advance objectives in Afghanistan obviously made the effort unique.By the end of the combat mission in 2011, needs for integrated strategic coordination, planning, and guidance, as well as requirements for interoperational departments were accepted and applied.These were necessary to produce integrated effects, or impacts, in the mission area.Notably, other countries involved in this North Atlantic Treaty Organization (NATO) commitment, such as the United States, faced similar challenges, which also resulted in adaptation and innovation.This article demonstrates that, despite Canada identifying and implementing these lessons during the Canadian combat mission The author would like to thank Brigadier-General (Retired) Serge Labbé, Colonel (Retired) Brett Boudreau, Major-General (Retired) Terrence "Terry" Liston, and Ms. Lindsay Coombs. 1 Stephen M. Saideman, "Lessons of History: What the Afghanistan
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.030 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".